91 lines
2.9 KiB
Markdown
91 lines
2.9 KiB
Markdown
---
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base_model: unsloth/Qwen2.5-1.5B-Instruct
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- qwen2.5
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license: apache-2.0
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language:
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- en
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- hi
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---
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As calling operations scale, it becomes clear that dialing and talking is not enough.
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Even with a strong voice AI + telephony architecture, the real value shows up only when post-call actions are captured and executed in a robust, dependable and consistent way. Closing the loop matters more than just connecting the call.
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To support that, we’re releasing our Hindi + English transcript analytics model tuned specifically for call transcripts:
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You can plug it into your calling or voice AI stack to automatically extract:
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• Enum-based classifications (e.g., call outcome, intent, disposition)
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• Conversation summaries
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• Action items / follow-ups
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It’s built to handle real-world Hindi, English, and mixed Hinglish calls, including noisy transcripts.
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Finetuning Parameters:
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```
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rank = 64
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lora_alpha = rank*2,
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target_modules = ["q_proj", "k_proj", "v_proj", "o_proj",
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"gate_proj", "up_proj", "down_proj",],
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SFTConfig(
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dataset_text_field = "prompt",
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per_device_train_batch_size = 32,
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gradient_accumulation_steps = 1, # Use GA to mimic batch size!
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warmup_steps = 5,
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num_train_epochs = 2,
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learning_rate = 2e-4,
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logging_steps = 50,
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optim = "adamw_8bit",
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weight_decay = 0.001,
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lr_scheduler_type = "linear",
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seed = SEED,
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report_to = "wandb",
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eval_strategy="steps",
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eval_steps=200,
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)
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The model was finetuned on ~100,000 curated transcripts across different domanins and language preferences
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```
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Provide the below schema for best output:
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```
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response_schema = {
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"type": "object",
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"properties": {
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"key_points": {
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"type": "array",
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"items": {"type": "string"},
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"nullable": True,
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},
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"action_items": {
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"type": "array",
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"items": {"type": "string"},
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"nullable": True,
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},
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"summary": {"type": "string"},
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"classification": classification_schema,
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},
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"required": ["summary", "classification"],
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}
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```
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- **Developed by:** RinggAI
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- **License:** apache-2.0
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- **Finetuned from model :** unsloth/Qwen2.5-1.5B-Instruct
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- Parameter decision where made using
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**Schulman, J., & Thinking Machines Lab. (2025).**
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*LoRA Without Regret.*
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Thinking Machines Lab: Connectionism.
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DOI: 10.64434/tml.20250929
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Link: https://thinkingmachines.ai/blog/lora/
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[<img style="border-radius: 20px;" src="https://storage.googleapis.com/desivocal-prod/desi-vocal/logo.png" width="200"/>](https://ringg.ai)
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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